Parallel Interference Cancellation is a known technique for cancelling interference from received wireless communication signals. For example, the technique has been suggested for the WCDMA uplink, in a paper by B. Hagerman, F. Gunnarsson, H. Murai, M. Tadenuma, and J. Karlsson, entitled “WCDMA Uplink Parallel Interference Cancellation—System Simulations and Prototype Field Trials,” published in the EURASIP Journal on Applied Signal Processing, 2005:11, pp. 1725-1735, which is incorporated herein in its entirety. PIC showed good performance in the WCDMA Uplink application, which is characterized by a homogeneous set of speech users. With High Speed Packet Access (HSPA), the mix of users can be highly heterogeneous, ranging from very low rate messaging to very high rate data users. PIC may be well suited for such a heterogeneous mix as well.
Consider a wireless communication receiver, receiving J signals (1, . . . , J) arriving simultaneously, and interfering with one another. An ideal receiver demodulates the J signals jointly; however, such a receiver cannot be realized in practice due to the enormous computational complexity of the task. A PIC structure is a practical way to approach the performance of a joint demodulator.
A PIC system receives the joint signals, comprising time samples from one or more receive antennas, and an interference data covariance matrix representing covariance properties between samples from different time delays and/or from different antennas. The PIC system incrementally cancels interference, isolating signals and improving the signal quality in successive stages. Each downstream stage performs better signal reconstruction than prior stages, as it starts with the improved signal from a prior stage, and in turn provides its results to a later stage for still better improvement. Each stage comprises one or more parallel modules, each module dedicated to isolating and reconstructing one of the J received communication signals. Within each module, all other J−1 signals are considered interference, and are cancelled out of the receiver input. As signals are cancelled out, the interference data covariance matrix must be updated correspondingly, to remove the covariance information associated with the cancelled signals. Updating the covariance matrix is a computationally demanding operation, which may limit the size and speed of the PIC system, thus limiting receiver performance.